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Cluster Analysis
Chapter 1: Introduction
1.1: Course Introduction (2:11)
1.2: Course Objective (1:23)
Chapter 2: Overview of Data Analytics Techniques
2.1: Overview of Data Analytics Tools (2:22)
2.2: Data Analytics Techniques (2:17)
Chapter 3: Data-driven Market Segmentation
3.1: Introduction to Data-driven Segmentation (1:49)
3.2: Activity: Using Scatter Plot with MobiSmart Data (2:56)
3.3: R 01 - Read Data (1:08)
3.4: R 02 - Scatter Plot (1:03)
Chapter 4: Cluster Analysis
4.1: What is Cluster Analysis? (2:59)
4.2: Dendogram (3:36)
4.3: R 03 - HAC (1:26)
4.4: R 04 - Dendrogram (1:26)
4.5: R 05 - Scree Plot (1:07)
4.6: Similarity Measures (3:23)
Chapter 5: Clustering Methods
5.1: Hierarchical Clustering (2:52)
5.2: Linkage in Hierarchical Clustering (3:13)
5.3: K-Means Clustering (3:07)
5.4: Activity: K-Means solution for MobiSmart (3:29)
5.5: R 06 - K-Means (1:08)
Chapter 6: Segmenting Markets
6.1: Identifying Market Segments (3:28)
6.2: Effective Segmentation (3:55)
6.3: Activity: MobiSmart - Segment Data (3:24)
Chapter 7: Clustering with Categorical Data
7.1: Clustering With Qualitative Data - Analysing Responses (3:02)
7.2: Clustering With Qualitative Data - Measuring association (4:03)
Chapter 8: Summary
8.1: Quiz
8.2: Summary (1:15)
7.2: Clustering With Qualitative Data - Measuring association
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